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Long run volatility forecasting for individual stocks in a one factor model

Engle, Robert F.; Lee, Gary G. J. - 1993

Persistent link: https://www.econbiz.de/10000877958

Forecasting intraday volatility in the US equity market : multiplicative component GARCH

Engle, Robert F.; Sokalska, Magdalena E. - In: Journal of financial econometrics : official journal of … 10 (2012) 1, pp. 54-83

Persistent link: https://www.econbiz.de/10009519713

Time-Varying Betas and Asymmetric Effect of News : Empirical Analysis of Blue Chip Stocks

Cho, Young-Hye - 1999

cross sectional variation and consequently lead to weak results. If the asymmetric effect is more readily apparent in daily …

Persistent link: https://www.econbiz.de/10012471454

Large dynamic covariance matrices: enhancements based on intraday data

De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2021 - This version: June 2021

Multivariate GARCH models do not perform well in large dimensions due to the so-called curse of dimensionality. The recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this paper, we show how...

Persistent link: https://www.econbiz.de/10012584099

Large dynamic covariance matrices: enhancements based on intraday data

De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2022 - This version: January 2022

Persistent link: https://www.econbiz.de/10013040932

Large dynamic covariance matrices: enhancements based on intraday data

De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2020

Modeling and forecasting dynamic (or time-varying) covariance matrices has many important applications in finance, such as Markowitz portfolio selection. A popular tool to this end are multivariate GARCH models. Historically, such models did not perform well in large dimensions due to the...

Persistent link: https://www.econbiz.de/10012253083